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At least 181 records · Page 10

Estimation of elastic aircraft parameters using the maximum likelihood method

The application of the maximum likelihood method to estimate the aerodynamic parameters of elastic flight vehicles in a symmetric flight condition is discussed. In this application, particular attention is directed toward the center of mass, elastic deformation, and sensor equations of motion. It is shown that the two major computational problems to be overcome are the inversion of large-sized matrices and the time-wise integration of a large number of linear, ordinary, differential equations.

Schwanz, R. C.↗

Maximum likelihood identification of aircraft stability and control derivatives

Application of a generalized identification method to flight test data analysis. The method is based on the maximum likelihood (ML) criterion and includes output error and equation error methods as special cases. Both the linear and nonlinear models with and without process noise are considered. The flight test data from lateral maneuvers of HL-10 and M2/F3 lifting bodies are processed to determine the lateral stability and control derivatives, instrumentation accuracies, and biases. A comparison is made between the results of the output error method and the ML method for M2/F3 data containing gusts. It is shown that better fits to time histories are obtained by using the ML method. The nonlinear model considered corresponds to the longitudinal equations of the X-22 VTOL aircraft. The data are obtained from a computer simulation and contain both process and measurement noise. The applicability of the ML method to nonlinear models with both process and measurement noise is demonstrated.

Mehra, R. K.↗

Practical aspects of using a maximum likelihood estimator

The application of a maximum likelihood estimator to flight data is discussed and procedures to facilitate routine analysis of a large amount of flight data are proposed. Flight data were used to demonstrate the proposed procedures. Modeling considerations are discussed for the system to be identified, including linear aerodynamics, instrumentation, and data time shifts, and aerodynamic biases for the specific types of maneuvers to be analyzed. Data editing to eliminate common data acquisition problems, and a method of identifying other problems are considered. The need for careful selection of the maneuver or portions of the maneuver to be analyzed is pointed out. Uncertaintly levels (analogous to Cramer-Rao bounds) are discussed as a way of recognizing significant new information.

Iliff, K. W.↗

Maximum likelihood failure detection techniques applied to the shuttle orbiter reaction control subsystem

A technique for on-board detection and identification of hard failures and leaks of the shuttle orbiter reaction control subsystem jets, during the orbital flight phase, is presented. The method uses gimbal angle and linear accelerometer measurements from the orbiter inertial measurement unit and requires no additional hardware. Extended Kalman filters with residual traps are employed for state estimation, and generalized likelihood ratio tests for jet failure identification. Rigid body simulation results indicate identification times of less than 2 seconds for hard jet failures and less than 70 seconds for jet leaks.

Deckert, J. C.↗

A multinomial maximum likelihood program /MUNOML/

A multinomial maximum likelihood program (MUNOML) for signal detection and for behavior models is discussed. It is found to be useful in day to day operation since it provides maximum flexibility with minimum duplicated effort. It has excellent convergence qualities and rarely goes beyond 10 iterations. A library of subroutines is being collected for use with MUNOML, including subroutines for a successive categories model and for signal detectability models.

Curry, R. E.↗

Practical aspects of a maximum likelihood estimation method to extract stability and control derivatives from flight data

A maximum likelihood estimation method was applied to flight data and procedures to facilitate the routine analysis of a large amount of flight data were described. Techniques that can be used to obtain stability and control derivatives from aircraft maneuvers that are less than ideal for this purpose are described. The techniques involve detecting and correcting the effects of dependent or nearly dependent variables, structural vibration, data drift, inadequate instrumentation, and difficulties with the data acquisition system and the mathematical model. The use of uncertainty levels and multiple maneuver analysis also proved to be useful in improving the quality of the estimated coefficients. The procedures used for editing the data and for overall analysis are also discussed.

Iliff, K. W.↗

Maximum likelihood convolutional decoding (MCD) performance due to system losses

A model for predicting the computational performance of a maximum likelihood convolutional decoder (MCD) operating in a noisy carrier reference environment is described. This model is used to develop a subroutine that will be utilized by the Telemetry Analysis Program to compute the MCD bit error rate. When this computational model is averaged over noisy reference phase errors using a high-rate interpolation scheme, the results are found to agree quite favorably with experimental measurements.

Webster, L.↗

Acreage estimation, feature selection, and signature extension dependent upon the maximum likelihood decision rule

A maximum likelihood estimation technique is used for the analysis of agricultural remote sensor data. The m-class probability of misclassification is estimated using unlabeled test samples and labeled training samples. A bound on the variance of a proposed unbiased estimator of the m-class probability of error is derived. The particular case in which each class density is assumed to be a mixture of multivariate normal densities is considered. The extension of spectral signatures in space and time is discussed.

Quirein, J. A.↗

Regions of constrained maximum likelihood parameter identifiability

This short paper considers the parameter-identification problem of general discrete-time, nonlinear, multiple input-multiple output dynamic systems with Gaussian white distributed measurement errors. Knowledge of the system parameterization is assumed to be available. Regions of constrained maximum likelihood (CML) parameter identifiability are established. A computation procedure employing interval arithmetic is proposed for finding explicit regions of parameter identifiability for the case of linear systems.

Lee, C.-H.↗

Performance and sensitivity analysis of the generalized likelihood ratio method for failure detection

Results of the generalized likelihood ratio (GLR) technique for the detection of failures in aircraft application are presented, and its relationship to the properties of the Kalman-Bucy filter is examined. Under the assumption that the system is perfectly modeled, the detectability and distinguishability of four failure types are investigated by means of analysis and simulations. Detection of failures is found satisfactory, but problems in identifying correctly the mode of a failure may arise. These issues are closely examined as well as the sensitivity of GLR to modeling errors. The advantages and disadvantages of this technique are discussed, and various modifications are suggested to reduce its limitations in performance and computational complexity.

Bueno, R. A.↗

Status report on the generalized likelihood ratio failure detection technique, with application to the F-8 aircraft

The generalized likelihood ratio technique, a scheme for detecting and identifying abrupt changes in dynamic systems, is described in detail. Attention is given to distinguishability, detectability, and sensitivity to modeling errors. This failure detection technique is applied to a two-dimensional model of the F-8, flying at Mach .6 at 20,000 ft. in cumulus clouds.

Bueno, R.↗

Further observations on maximum likelihood estimates of stability and control characteristics obtained from flight data

A maximum likelihood estimation method for flight test data is described. Flight results based on 3000 maneuvers from 30 aircraft on the effect of resolution and sampling rate on the estimates, on understanding the discrepancies previously observed in the magnitude of the Cramer-Rao bounds, on the scale effects on the derivative estimates obtained from dynamic aircraft flight maneuvers, and on the analysis of lateral-directional maneuvers obtained in turbulence, are presented.

Iliff, K. W.↗

DSN telemetry system performance using a maximum likelihood convolutional decoder

Results are described of telemetry system performance testing using DSN equipment and a Maximum Likelihood Convolutional Decoder (MCD) for code rates 1/2 and 1/3, constraint length 7 and special test software. The test results confirm the superiority of the rate 1/3 over that of the rate 1/2. The overall system performance losses determined at the output of the Symbol Synchronizer Assembly are less than 0.5 db for both code rates. Comparison of the performance is also made with existing mathematical models. Error statistics of the decoded data are examined. The MCD operational threshold is found to be about 1.96 db.

Benjauthrit, B.↗

Maximum-likelihood data decoder

Digital convolutional decoder circuit for data communication receiver employs Viterbi decoding algorithm to quickly and efficiently decode data on basis of "maximum likelihood" computations.

Alberda, M. E.↗

A maximum likelihood convolutional decoder model vs experimental data comparison

This article describes the comparison of a maximum likelihood convolutional decoder (MCD) prediction model and the actual performance of the MCD at the Madrid Deep Space Station. The MCD prediction model is used to develop a subroutine that has been utilized by the Telemetry Analysis Program (TAP) to compute the MCD bit error rate for a given signal-to-noise ratio. The results indicate that that the TAP can predict quite well compared to the experimental measurements. An optimal modulation index also can be found through TAP.

Chen, R. Y.↗

Approximate maximum likelihood decoding of block codes

Approximate maximum likelihood decoding algorithms, based upon selecting a small set of candidate code words with the aid of the estimated probability of error of each received symbol, can give performance close to optimum with a reasonable amount of computation. By combining the best features of various algorithms and taking care to perform each step as efficiently as possible, a decoding scheme was developed which can decode codes which have better performance than those presently in use and yet not require an unreasonable amount of computation. The discussion of the details and tradeoffs of presently known efficient optimum and near optimum decoding algorithms leads, naturally, to the one which embodies the best features of all of them.

Greenberger, H. J.↗

Maximum likelihood estimation for life distributions with competing failure modes

Systems which are placed on test at time zero, function for a period and die at some random time were studied. Failure may be due to one of several causes or modes. The parameters of the life distribution may depend upon the levels of various stress variables the item is subject to. Maximum likelihood estimation methods are discussed. Specific methods are reported for the smallest extreme-value distributions of life. Monte-Carlo results indicate the methods to be promising. Under appropriate conditions, the location parameters are nearly unbiased, the scale parameter is slight biased, and the asymptotic covariances are rapidly approached.

Sidik, S. M.↗